Alternative Normalized-Preconditioning for Scalable Iterative Large-MIMO Detection

Jiuyu Liu; Yi Ma; Rahim Tafazolli

doi:10.48550/arxiv.2308.11321

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Alternative Normalized-Preconditioning for Scalable Iterative Large-MIMO Detection

Jiuyu Liu, Yi Ma and Rahim Tafazolli

22/08/2023

DOI: https://doi.org/10.48550/arxiv.2308.11321

Abstract

Signal detection in large multiple-input multiple-output (large-MIMO) systems presents greater challenges compared to conventional massive-MIMO for two primary reasons. First, large-MIMO systems lack favorable propagation conditions as they do not require a substantially greater number of service antennas relative to user antennas. Second, the wireless channel may exhibit spatial non-stationarity when an extremely large aperture array (ELAA) is deployed in a large-MIMO system. In this paper, we propose a scalable iterative large-MIMO detector named ANPID, which simultaneously delivers 1) close to maximum-likelihood detection performance, 2) low computational-complexity (i.e., square-order of transmit antennas), 3) fast convergence, and 4) robustness to the spatial non-stationarity in ELAA channels. ANPID incorporates a damping demodulation step into stationary iterative (SI) methods and alternates between two distinct demodulated SI methods. Simulation results demonstrate that ANPID fulfills all the four features concurrently and outperforms existing low-complexity MIMO detectors, especially in highly-loaded large MIMO systems.

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Title: Alternative Normalized-Preconditioning for Scalable Iterative Large-MIMO Detection
Creators: Jiuyu Liu - University of Surrey, School of Computer Science and Electronic Engineering
Yi Ma - University of Surrey, School of Computer Science and Electronic Engineering
Rahim Tafazolli - University of Surrey, School of Computer Science and Electronic Engineering
Grant note: This work is partially funded by the 5G Innovation Centre and 6G Innovation Centre.
Identifiers: 99812232102346
Copyright: The URI http://arxiv.org/licenses/nonexclusive-distrib/1.0/ is used to record the fact that the submitter granted the following license to arXiv.org on submission of an article: I grant arXiv.org a perpetual, non-exclusive license to distribute this article. I certify that I have the right to grant this license. I understand that submissions cannot be completely removed once accepted. I understand that arXiv.org reserves the right to reclassify or reject any submission.
Academic Unit: School of Computer Science and Electronic Engineering
Language: English
Resource Type: Preprint

Alternative Normalized-Preconditioning for Scalable Iterative Large-MIMO Detection

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